Introduction to Cancer Genetics and Genomics

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Introduction to Cancer Genetics and Genomics. Apostolos Psychogios, MD, FACMG Associate Professor of Pediatrics LeeAnne Brown Chair of Clinical Excellence Division of Medical Genetics and Genomic Medicine. Disclosure Statement of Financial Interest. - PowerPoint PPT Presentation

Transcript of Introduction to Cancer Genetics and Genomics

Introduction to Cancer Genetics and Genomics

Apostolos Psychogios, MD, FACMG

Associate Professor of Pediatrics

LeeAnne Brown Chair of Clinical Excellence

Division of Medical Genetics and Genomic Medicine

Disclosure Statement of Financial Interest

• I, Apostolos Psychogios, DO NOT have a financial

interest/arrangement or affiliation with one or more organizations

that could be perceived as a real or apparent conflict of interest

in the context of the subject of this presentation.

• I, Apostolos Psychogios, DO NOT anticipate discussing the

unapproved/investigative use of a commercial product/device

during this activity or presentation.

Learning Objectives

• Identify the genetic syndromes associated with breast, ovarian, colon and

other types of cancer and the genes associated with these syndromes.

• Use and understand the models available to predict risk of breast and

colon cancer.

• Understand the principles of genetic testing for individuals and families

where hereditary cancer predisposition is suspected.

• Recognize when to refer an individual or family for cancer genetics

evaluation

• Understand the management options for individuals who are carriers of

deleterious gene mutations

Inherited Predisposition to Cancer

• Inherited cancers range from 1-60%.

• For most tumor types, e.g. breast, the inherited

fraction fall in the range of 1-10%.

• Several rare tumors, adrenocortical carcinoma,

retinoblastoma, and optic gliomas have very

high inherited fraction (40-60%).

• Autosomal dominant inheritance

Inheritance Patterns

>10% Germline Mutations and Tumors

Multiple Mechanisms: Wilm’s Tumor

Multiple Mechanisms: Renal Cell Cancer

• Von Hippel Lindau Syndrome (VHL) – almost always clear cell histology

• 80% of sporadic RCC has somatic VHL mutations. Balanced translocation carriers involving chromosome 3

• Papillary renal carcinoma – due to activating mutations in c-MET oncogene

• Hereditary leiomyomatosis RCC: mutations in fumarate hydratase; autosomal dominant uterine fibroids and cutaneous leiomyomata

• Birt-Hogg-Dubé Syndrome – chromophobe/oncocytic

Multiple Cancers: Birt-Hogg-Dubé Syndrome

• Chromophobe/oncocytic

histology RCC

• Benign fibrofolliculomas

• Colonic polyps

• Medullary thyroid cancer

• Spontaneous pneumothorax

• BHD tumor suppressor gene

NEJM 359;7 August 14, 2008

Chromosomal Abnormalities in Human Cancer

Example of Imprecise Translocation: t(8;14) in Burkitt’s Lymphoma

Example of Precise Translocation: Philadelphia Chromosome in CML

Precise Translocation: t(11;22) in Ewings’ sarcoma

Large destructive lesion in the diaphysis or metaphysis with a moth-eaten

appearance periosteal lifting may give "onion skin" or "sunburst" appearance

N Engl J Med 2008;359:2143-53.

Genes and Common Cancers

Breast-Cancer Susceptibility Loci and Genes

N Engl J Med 2008;359:2143-53.

N Engl J Med 2007;357:154-62.

“Red Flags” for HBOC Syndrome

• Breast cancer diagnosed < 50 years

• Ovarian cancer

• Male breast cancer

• Two primary breast cancers

• “Triple-negative” breast cancer

• Ashkenazi Jewish ancestry

• Familial BRCA gene mutation

Risk Prediction Models

• There are well established computer models to

predict:– Risk of developing breast cancer for someone of “average” risk –

Gail Model.

– Risk of developing breast cancer based on family history – Claus

Tables.

– Likelihood that genetic testing will yield a mutation in BRCA1 or

BRCA2 – BRCAPro (US model) and BOADICEA (UK model).

N Engl J Med 2007;357:154-62.

Professional Societies Guidelines

N Engl J Med 2007;357:154-62.

Other Syndromes with Increased Risk for Breast Cancer

• Li-Fraumeni – average diagnosis 32 in p53 carriers

• Cowden’s syndrome – PTEN mutations assoc. with thyroid cancer, hamartomas, skin lesions

• Peutz-Jeghers – 32% by age 60

• Ataxia telangiectasia (ATM) heterozygotes.

Li-Fraumeni Syndrome (LFS)

Cowden Syndrome (CS)

• Breast Cancer risk (30% lifetime risk).

• Thyroid cancer (10% lifetime risk).

• Cerebellar dysplastic gangliocytoma

• Mucocutaneous lesions

• Trichilemmomas (facial)

• Papillomatous lesions

Colorectal Cancer (CRC) Risks

HNPCC Family Pedigree

Hereditary Non-Polyposis Colon Cancer Lynch Syndrome

• Autosomal dominant CRC without polyposis associated with

endometrial cancer, bile duct, ovarian, ureteral and gliomas.

• ~70% lifetime risk of CRC

• 50-70% endometrial cancer in classic Lynch.

• Right-sided CRC cancer is more frequent.

• Better prognosis of CRC stage for stage.

• Patients with 2 or 3 different primary HNPCC-related tumors.

“Red Flags” for an Affected Individual with HNPCC

Family History (Unaffected Individual) Criteria for HNPCC

Amsterdam Criteria (CRC based) - Exclude FAP

I. At least one CRC < age 50

II. Two affected generations

III. Three affected relatives, two are FDR relatives of other one

HNPCC Genes

Polyposis Syndromes

“Red Flags” for Polyposis Syndromes

• More than 10 cumulative colorectal adenomas

• Colorectal cancer associated with multiple adenomas

• Familial mutation for hereditary polyposis syndrome

HNPCC vs. AFAP vs. MAP

Polyposis Associated with FAP

MYH-Associated Polyposis

ACMG Genetics Review Course

Colorectal Cancer Management

“Red Flags” for Hereditary Melanoma

• Two or more melanomas in the proband or family (FDR)

• Melanoma and pancreatic cancer in the proband or family

• Family history of p16 gene mutation

Hereditary Melanoma

Genomics and the Continuum of Cancer Care

NEJM 2011;364:340-50.

N Engl J Med 2011;364:340-50.

N Engl J Med 2008;358:1148-59

N Engl J Med 2008;358:1148-59

N Engl J Med 2008;358:1148-59

Quillen Genomic Medicine Program

Research

LeeAnne Brown Research Project

• In collaboration with Mayo Clinic (Dr. Eric Wieben) 2012-2015

• Whole Exome Sequencing/Methylation Analysis of patients

with:

– Unknown syndromes

– Autism, intellectual disability

– Neurologic disorders (MS, ALS, AD)

– Tumors (Multiplex families with breast, prostate, bladder cancer)

Questions?